Least absolute relative error estimation for functional quadratic multiplicative model

Minimum miscibility pressure (MMP), which plays an important role in miscible flooding, is a key parameter in determining whether crude oil and gas are completely miscible. On the basis of 210 groups of CO2-crude oil system minimum miscibility pressure data, an improved CO2-crude oil system minimum miscibility pressure correlation was built by modified conjugate gradient method and global optimizing method. The new correlation is a uniform empirical correlation to calculate the MMP for both thin oil and heavy oil and is expressed as a function of reservoir temperature, C7+molecular weight of crude oil, and mole fractions of volatile components (CH4and N2) and intermediate components (CO2, H2S, and C2~C6) of crude oil. Compared to the eleven most popular and relatively high-accuracy CO2-oil system MMP correlations in the previous literature by other nine groups of CO2-oil MMP experimental data, which have not been used to develop the new correlation, it is found that the new empirical correlation provides the best reproduction of the nine groups of CO2-oil MMP experimental data with a percentage average absolute relative error (%AARE) of 8% and a percentage maximum absolute relative error (%MARE) of 21%, respectively.

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Investigating three sources of bias in hook-and-line surveys: survey design, gear saturation, and multispecies interactions

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/cjfas-2017-0286 ◽

2019 ◽

Vol 76 (2) ◽

pp. 192-207

Author(s):

Peter T. Kuriyama ◽

Trevor A. Branch ◽

Allan C. Hicks ◽

John H. Harms ◽

Owen S. Hamel

Keyword(s):

Interspecific Competition ◽

Population Size ◽

Relative Error ◽

Statistical Power ◽

Survey Design ◽

Biological Information ◽

Catch Per Unit Effort ◽

Absolute Relative Error ◽

Survey Results ◽

Survey Methodologies

Hook-and-line surveys can be used to estimate population trends in fish species where conventional methods such as trawl, acoustic, visual, or pot surveys cannot be applied. Hook-and-line surveys allow for the collection of biological information, but the resultant indices of abundance may be biased. We designed simulations to address concerns around survey design, hook saturation, and competition among species and found that catch per unit effort (CPUE) declined more slowly than population size across all scenarios. This hyperstability was most prominent when fish were found in high-density patches, and these scenarios have median absolute relative error values roughly three to five times greater than those with more even distributions of fish density. Despite hyperstability, the surveys still had statistical power to detect changes in abundance. Interspecific competition for hooks caused bias in survey results when one species was more aggressive than another. Taken together, our results indicate hook-and-line surveys fill a niche in survey methodologies, but their use and interpretation can be challenged by hyperstability and competition among species.

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Bayesian network model for flood forecasting based on atmospheric ensemble forecasts

Natural Hazards and Earth System Science ◽

10.5194/nhess-19-2513-2019 ◽

2019 ◽

Vol 19 (11) ◽

pp. 2513-2524 ◽

Cited By ~ 3

Author(s):

Leila Goodarzi ◽

Mohammad E. Banihabib ◽

Abbas Roozbahani ◽

Jörg Dietrich

Keyword(s):

Bayesian Network ◽

Relative Error ◽

Wrf Model ◽

Cumulus Parameterization ◽

Small Data ◽

Ensemble Forecasts ◽

Validation Data ◽

Flood Peak ◽

Absolute Relative Error ◽

Cumulus Parameterization Schemes

Abstract. The purpose of this study is to propose the Bayesian network (BN) model to estimate flood peaks from atmospheric ensemble forecasts (AEFs). The Weather Research and Forecasting (WRF) model was used to simulate historic storms using five cumulus parameterization schemes. The BN model was trained to compute flood peak forecasts from AEFs and hydrological pre-conditions. The mean absolute relative error was calculated as 0.076 for validation data. An artificial neural network (ANN) was applied for the same problem but showed inferior performance with a mean absolute relative error of 0.39. It seems that BN is less sensitive to small data sets, thus it is more suited for flood peak forecasting than ANN.

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Multicriterion assessment framework of flood events simulated with the vertically mixed runoff model in semiarid catchments in the middle Yellow River

10.5194/nhess-2018-402 ◽

2019 ◽

Author(s):

Dayang Li ◽

Zhongmin Liang ◽

Yan Zhou ◽

Binquan Li ◽

Yupeng Fu

Keyword(s):

Relative Error ◽

Yellow River ◽

Performance Criterion ◽

Generation Mechanism ◽

Limited Information ◽

Assessment Framework ◽

Flood Events ◽

Runoff Generation ◽

Absolute Relative Error ◽

Runoff Model

Abstract. Flood forecasting and simulation in semiarid regions are always poor, and a single criterion assessment provides limited information for decision making. Here, we propose a multicriterion assessment framework combining the absolute relative error, the flow partitioning and the confidence interval estimated by the Hydrologic Uncertainty Processor (HUP) to assess the most striking feature of an event-based flood–the peak flow. The physically based model MIKE SHE and three conceptual models (two models with a single runoff generation mechanism, the Xi’anjiang model (XAJ) and the Shanbei model (SBM), and one model with the mixed runoff generation mechanism, the vertically mixed runoff model (VMM)) are compared in terms of flood modeling performance in four semiarid catchments (Qiushui River, Qingjian River, Tuwei River and Kuye River) in the middle Yellow River. Our results show that VMM has a better flood estimation performance than the other models, and under the multicriterion assessment framework, the average acceptance of flood events accounts for 58 %, but when absolute relative error 20 % is used as the performance criterion, its figure is only 41 % in four semiarid catchments.

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Constitutive Equations for Describing the Warm and Hot Deformation Behavior of 20Cr2Ni4A Alloy Steel

Metals ◽

10.3390/met10091169 ◽

2020 ◽

Vol 10 (9) ◽

pp. 1169

Author(s):

Haoran Wang ◽

Wei Wang ◽

Ruixue Zhai ◽

Rui Ma ◽

Jun Zhao ◽

...

Keyword(s):

Flow Stress ◽

Alloy Steel ◽

Relative Error ◽

Constitutive Equations ◽

Type Equation ◽

Coefficient Of Determination ◽

Original Strain ◽

Compression Tests ◽

Absolute Relative Error ◽

Average Absolute Relative Error

Isothermal hot compression tests of 20Cr2Ni4A alloy steel were performed under temperatures of 973–1273 K and strain rates of 0.001–1 s−1. The behavior of the flow stress of 20Cr2Ni4A alloy steel at warm and hot temperatures is complicated because of the influence of the work hardening, the dynamic recovery, and the dynamic recrystallization. Four constitutive equations were used to predict the flow stress of 20Cr2Ni4A alloy steel, including the original strain-compensated Arrhenius-type (osA-type) equation, the new modified strain-compensated Arrhenius-type (msA-type) equation, the original Hensel–Spittel (oHS) equation and the modified Hensel–Spittel (mHS) equation. The msA-type and mHS are developed by revising the deformation temperatures, which can improve prediction accuracy. In addition, we propose a new method of solving the parameters by combining a linear search with multiple linear regression. The new solving method is used to establish the two modified constitutive equations instead of the traditional regression analysis. A comparison of the predicted values based on the four constitutive equations was performed via relative error, average absolute relative error (AARE) and the coefficient of determination (R2). These results show the msA-type and mHS equations are more accurate and efficient in terms of predicting the flow stress of the 20Cr2Ni4A steel at elevated temperature.

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Estimating the mass of CMEs from the analysis of EUV dimmings

Astronomy and Astrophysics ◽

10.1051/0004-6361/201834163 ◽

2019 ◽

Vol 627 ◽

pp. A8 ◽

Cited By ~ 1

Author(s):

F. M. López ◽

H. Cremades ◽

L. A. Balmaceda ◽

F. A. Nuevo ◽

A. M. Vásquez

Keyword(s):

Relative Error ◽

White Light ◽

Line Of Sight ◽

Absolute Relative Error ◽

Empirical Function ◽

Alternative Means ◽

Extreme Uv ◽

The Masses ◽

Coronal Dimming

Context. Reliable estimates of the mass of coronal mass ejections (CMEs) are required to quantify their energy and predict how they affect space weather. When a CME propagates near the observer’s line of sight, these tasks involve considerable errors, which motivated us to develop alternative means for estimating the CME mass. Aims. We aim at further developing and testing a method that allows estimating the mass of CMEs that propagate approximately along the observer’s line of sight. Methods. We analyzed the temporal evolution of the mass of 32 white-light CMEs propagating across heliocentric heights of 2.5–15 R⊙, in combination with that of the mass evacuated from the associated low coronal dimming regions. The mass of the white-light CMEs was determined through existing methods, while the mass evacuated by each CME in the low corona was estimated using a recently developed technique that analyzes the dimming in extreme-UV (EUV) images. The combined white-light and EUV analyses allow the quantification of an empirical function that describes the evolution of CME mass with height. Results. The analysis of 32 events yielded reliable estimates of the masses of front-side CMEs. We quantified the success of the method by calculating the relative error with respect to the mass of CMEs determined from white-light STEREO data, where the CMEs propagate close to the plane of sky. The median for the relative error in absolute values is ≈30%; 75% of the events in our sample have an absolute relative error smaller than 51%. The sources of uncertainty include the lack of knowledge of piled-up material, subsequent additional mass supply from the dimming region, and limitations in the mass-loss estimation from EUV data. The proposed method does not rely on assumptions of CME size or distance to the observer’s plane of sky and is solely based on the determination of the mass that is evacuated in the low corona. It therefore represents a valuable tool for estimating the mass of Earth-directed events.

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